Authors

Abstract

Intensive nitrogen (N) fertilizer application in the vegetable fields of China has commonly occurred during recent decades and may substantially increase both nitrous oxide (N2O) and nitric oxide (NO) emissions. However, the quantification of N2O and NO emissions from vegetable fields has been rare due to both the lack of long-term field measurements and reliable methods for extrapolating these measurements. Using a unique dataset from a four-year measurement study of an intensively managed conventional vegetable field in southeastern China, we tested a process-based biogeochemical model, denitrification-decomposition (DNDC), for its applicability for quantifying the impact of fertilizer management practices on emissions of N trace gases from vegetable production. The results from the model validation indicate that the simulations of vegetable yields and seasonal cumulative N2O and NO emissions are consistent with the observations. In addition, DNDC can generally capture the measured temporal pattern of daily N2O and NO fluxes. The modeled impacts of fertilization alternatives can be summarized as follows: (a) both the type and application rate of N fertilizers play important roles in regulating N2O and NO emissions as well as vegetable growth; (b) reducing the N application rate to 75% of the conventional amount decreased N2O and NO emissions by 31% and showed little impact on vegetable biomasses, suggesting that reducing the N dose to a reasonable level would be advisable for both the mitigation of N gases emissions and the maintenance of vegetable production; and (c) replacing synthetic fertilizer under the conventional management practices with organic manure may significantly stimulate N2O emission by 62% while decreasing vegetable yields. The results from this modeling study may provide useful information for the ongoing debate regarding the optimization of fertilizer use strategies in China. This study also demonstrates the potential of utilizing process-based models, such as DNDC, to quantify and mitigate N2O and NO emissions from intensive vegetable production through interpreting, integrating, and extrapolating field observations.